Look-ahead intelligent energy management of a parallel hybrid electric vehicle

Improving fuel efficiency in vehicles can reduce the energy consumption concerns associated with operating the vehicles. This paper presents a model for a parallel hybrid electric vehicle. In the model, the flow of energy starts from wheels and spreads toward engine and electric motor. A fuzzy logic based control strategy is implemented for the vehicle. The controller manages the energy flow from the engine and the electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines the vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. It then determines the best values for continuous variable transmission ratio, speed, and torque. A slope window method is formed that takes into account the look-ahead slope information, and determines the best vehicle speed. The developed model and control strategy are simulated using real highway data relating to Nowra-Bateman Bay in Australia, and SAE Highway Fuel Economy Driving Schedule. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces the fuel consumption of the vehicle.

Risk of falls and motor vehicle collisions in glaucoma

PURPOSE. To investigate the risk of falls and motor vehicle collisions (MVCs) in patients with glaucoma.

METHODS. The sample comprised 48 patients with glaucoma (mean visual field mean deviation [MD] in the better eye = −3.9 dB; 5.1 dB SD) and 47 age-matched normal control subjects, who were recruited from a university-based hospital eye care clinic and are enrolled in an ongoing prospective study of risk factors for falls, risk factors for MVCs, and on-road driving performance in glaucoma. Main outcome measures at baseline were previous self-reported falls and MVCs, and police-reported MVCs. Demographic and medical data were obtained. In addition, functional independence in daily living, physical activity level and balance were assessed. Clinical vision measures included visual acuity, contrast sensitivity, standard automated perimetry, useful field of view (UFOV), and stereopsis. Analyses of falls and MVCs were adjusted to account for the possible confounding effects of demographic characteristics, medications, and visual field impairment. MVC analyses were also adjusted for kilometers driven per week.

RESULTS. There were no significant differences between patients with glaucoma and control subjects with respect to number of systemic medical conditions, body mass index, functional independence, and physical activity level (P > 0.10). At baseline, 40 (83%) patients with glaucoma and 44 (94%) control subjects were driving. Compared with control subjects, patients with glaucoma were over three times more likely to have fallen in the previous year (odds ratio [OR]adjusted = 3.71; 95% CI, 1.14–12.05), over six times more likely to have been involved in one or more MVCs in the previous 5 years (ORadjusted = 6.62; 95% CI, 1.40–31.23), and more likely to have been at fault (ORadjusted = 12.44; 95% CI, 1.08–143.99). The strongest risk factor for MVCs in patients with glaucoma was impaired UFOV selective attention (ORadjusted = 10.29; 95% CI, 1.10–96.62; for selective attention >350 ms compared with ≤350 ms).

CONCLUSIONS. There is an increased risk of falls and MVCs in patients with glaucoma.

Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved.

Occupational light vehicle-use: a research driven strategy to improve surveillance and inform policy

Background: Occupational light vehicles (OLV) are light passenger and loadshaped vehicles used for work. The OLV-associated injury burden is as great as that of heavy vehicle users, but has been largely ignored by occupational health and safety (OHS) regulators. Contingent employment growth has accentuated existing gaps in the policy framework between OHS and road-safety. Frequent burden shifting from OHS to road-related health systems undermines the evidence base necessary to inform policy development. Aims: To provide evidence-based recommendations for the collection of OLVuser surveillance data and to underpin OHS procedures and policies for OLVusers. Method: The literature was systematically analyzed to identify OLV-user OHS policy and practice gaps. Strategies to improve and co-ordinate surveillance systems were developed to address the identified limitations. Results: Gaps were identified in OLV-user legislation, data collection, and riskmanagement. These require strategies to improve identification of all OLV-users and to co-ordinate surveillance and OHS practice. Discussion: Contemporary reform of road and OHS, policy, provides a timely opportunity for the implementation of strategic responses to this serious road safety and occupational, public health problem.

Occupational light vehicle use: characterising the at-risk population

Previous occupational light vehicle research has concentrated on employees using cars. The aim of this study was to identify and characterise the total occupational light vehicle-user population and compare it with the privately-used light vehicle population. Occupational light vehicle and private light vehicle populations were identified through use-related 2003 registration categories from New South Wales Roads and Traffic Authority data. Key groups of occupational light vehicle registration variables were comparatively assessed as potential determinants of occupational light vehicleuser risks. These comparisons were expressed as odds ratios with 95% Confidence Intervals. The occupational light vehicle population vehicles (n=646,201) comprised 18% of all light vehicle registrations. A number of statistical differences emerge between the two populations. For instance, 86% of occupational light vehicle registrants were male versus 65% of private registrants, and 56% of the occupational users registered load shape vehicles versus 20% of the private registrants. Occupational light vehicles registered for farming or taxi use were more than six times more likely to belong to sole-traders than organisations. Sole-traders were nearly twice as likely to register light-trucks, and twice as likely to register older vehicles, than organisations. This study demonstrates that the occupational light vehicle user population is larger and more diverse than previously shown with characteristics likely to increase the relative risks of motor vehicle crashes. More occupational light vehicles were load shapes and therefore likely to have poorer crashworthiness ratings than cars. Occupational light vehicles are frequently used by sole-traders for activities with increased OHS risks including farming and taxi use. Further exploration of occupational light vehicle-user crash risks should include all vehicle types, work arrangements and small ‘fleets’.

Occupational light-vehicle use and OHS legislative frameworks : an Australian example

Occupational light vehicle (OLV) use and associated exposures and hazards in the Australian context are described. Available insurance data indicate that the OLV injury burden, which is greater than that of other work–road users, is growing asOLV use changes incidental, to workers', primary occupations and work patterns. Legislation that affects OLV users is reviewed and the shifting of the burden of responsibility for injured or killed OLV users between workers' compensation, motor accident insurance and public health systems is described. Changes to OHS regulatory frameworks are proposed to better address OLV-relevant policy and practice. These issues are relevant for many international jurisdictions.

Use of weekly assessment data to enhance evaluation of a subjective wellbeing intervention

PURPOSE: While intervention effects in target outcomes have typically been tested based on change from baseline to post-intervention, such approaches typically ignore individual differences in change, including time taken to see improvement. The present study demonstrates how weekly patient-reported data may be used to augment traditional pre-post intervention evaluations in order to gain greater insights into treatment efficacy. METHODS: Two hundred and fifty-two adolescent boys and girls (M age = 13.6 years, SD = 0.6 years) from four secondary schools in Victoria, Australia, were assigned by school into control (n = 88) or intervention (n = 164) groups. The intervention group participated in a 6-week course designed to improve subjective wellbeing (SWB) by fostering resilience, coping skills, and self-esteem. In addition to baseline, post-intervention, and 3-month follow-up assessments of SWB, intervention group participants also completed weekly summarise of affective experiences for the duration of the intervention phase. RESULTS: While standard pre-post data showed significant improvement in SWB for the intervention group relative to controls, weekly data showed individual differences in the trajectory of change during this intervention phase; low SWB individuals experienced initial worsening of symptoms followed by improvement in the second half of the intervention phase, whereas high SWB individuals experienced initial gains, followed by a plateau from Week 4 onwards. CONCLUSIONS: Addition of weekly data provided greater insights into intervention effects by: (1) contradicting the notion that early responsiveness to treatment is predictive of level of improvement by post-intervention, and (2) providing data-based insights into ways to enhance the intervention.

Trajectory of sedation assessment and sedative use in intubated and ventilated patients in intensive care: a clinical audit

Background: Sedation is crucial for the recovery of patients in intensive care units (ICUs). Maintaining comfort and safety promotes optimal care for critically ill patients. Purpose: To examine sedation assessment and management undertaken by health professionals for mechanically ventilated patients in one Australian ICU. Methods: A retrospective clinical audit was undertaken of medical records of all eligible, mechanically ventilated patients admitted to an ICU of an Australian metropolitan, teaching hospital over a 12-month period. A Sedation Audit Tool was used to collect data from the day of intubation to 5 days after intubation. Findings: Data were extracted from medical records of 150 patients. The Riker Sedation-Agitation Scale (SAS) was the scoring system used. Patients were unarousable or very sedated between 57% and 81% at some point during the study period, while between 5% and 11% were agitated, very agitated or extremely agitated across this time. Patients' sedation scores were not documented in between 3.3% and 23.3% of patients. Medications commonly used were propofol, midazolam, morphine, and fentanyl. There were 135 situations of adverse events, which related to patients pulling endotracheal tubes leading to malpositioning, patients biting endotracheal tubes causing desaturation, patient experiencing excessive agitation requiring restraint use, patients experiencing increased intracranial pressure above desired limits, patients self-extubating, and patients experiencing over-drowsiness leading to delays in extubation. Conclusions: Many patients were either very sedated or agitated at some point during the study period, and some patients experienced adverse outcomes associated with sedation practices. The findings inform future quality initiatives to improve sedation practices.

The trajectory of dispersal research in conservation biology. Systematic review

Dispersal knowledge is essential for conservation management, and demand is growing. But are we accumulating dispersal knowledge at a pace that can meet the demand? To answer this question we tested for changes in dispersal data collection and use over time. Our systematic review of 655 conservation-related publications compared five topics: climate change, habitat restoration, population viability analysis, land planning (systematic conservation planning) and invasive species. We analysed temporal changes in the: (i) questions asked by dispersal-related research; (ii) methods used to study dispersal; (iii) the quality of dispersal data; (iv) extent that dispersal knowledge is lacking, and; (v) likely consequences of limited dispersal knowledge. Research questions have changed little over time; the same problems examined in the 1990s are still being addressed. The most common methods used to study dispersal were occupancy data, expert opinion and modelling, which often provided indirect, low quality information about dispersal. Although use of genetics for estimating dispersal has increased, new ecological and genetic methods for measuring dispersal are not yet widely adopted. Almost half of the papers identified knowledge gaps related to dispersal. Limited dispersal knowledge often made it impossible to discover ecological processes or compromised conservation outcomes. The quality of dispersal data used in climate change research has increased since the 1990s. In comparison, restoration ecology inadequately addresses large-scale process, whilst the gap between knowledge accumulation and growth in applications may be increasing in land planning. To overcome apparent stagnation in collection and use of dispersal knowledge, researchers need to: (i) improve the quality of available data using new approaches; (ii) understand the complementarities of different methods and; (iii) define the value of different kinds of dispersal information for supporting management decisions. Ambitious, multi-disciplinary research programs studying many species are critical for advancing dispersal research.

Cooperative data scheduling in hybrid vehicular ad hoc networks: VANET as a software defined network

This paper presents the first study on scheduling for cooperative data dissemination in a hybrid infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communication environment. We formulate the novel problem of cooperative data scheduling (CDS). Each vehicle informs the road-side unit (RSU) the list of its current neighboring vehicles and the identifiers of the retrieved and newly requested data. The RSU then selects sender and receiver vehicles and corresponding data for V2V communication, while it simultaneously broadcasts a data item to vehicles that are instructed to tune into the I2V channel. The goal is to maximize the number of vehicles that retrieve their requested data. We prove that CDS is NP-hard by constructing a polynomial-time reduction from the Maximum Weighted Independent Set (MWIS) problem. Scheduling decisions are made by transforming CDS to MWIS and using a greedy method to approximately solve MWIS. We build a simulation model based on realistic traffic and communication characteristics and demonstrate the superiority and scalability of the proposed solution. The proposed model and solution, which are based on the centralized scheduler at the RSU, represent the first known vehicular ad hoc network (VANET) implementation of software defined network (SDN) concept.

An aggravated trajectory of depression and anxiety co-morbid with Hepatitis C: a within-groups study of 61 Australian outpatients.

BACKGROUND: This study aimed to explore the course of depression and anxiety in chronic hepatitis C patients. METHODS:   Data were combined from two studies: (1) Hospital Anxiety and Depression Scale (HADS) scores in 395 consecutive Australian outpatients from 2006 to 2010 formed the baseline measurement; and (2) Depression Anxiety Stress Scales (DASS) scores in a survey of a sub-sample of these patients in 2011 formed the follow-up measurement. After converting DASS to HADS scores, changes in symptom scores and rates of case-ness (≥8), and predictors of follow-up symptoms were assessed. RESULTS:   Follow-up data were available for 61 patients (70.5% male) whose age ranged from 24.5 to 74.6 years (M=45.6). The time to follow-up ranged from 20.7 to 61.9 months (M=43.8). Baseline rates of depression (32.8%) and anxiety (44.3%) increased to 62.3% and 67.2%, respectively. These findings were confirmed, independent of the conversion, by comparing baseline HADS and follow-up DASS scores with British community norms. Baseline anxiety and younger age predicted depression, while baseline anxiety, high school non-completion, and single relationship status predicted anxiety. CONCLUSION:  This study demonstrated a worsening trajectory of depression and anxiety. Further controlled and prospective research in a larger sample is required to confirm these findings.